When addressing AI's 'black box' problem, lawmaker Alex Boris suggests regulators should bypass the philosophical debate over a model's 'intent.' The focus should be on its observable impact. By setting up tests in controlled environments—like telling an AI it will be shut down—you can discover and mitigate dangerous emergent behaviors before release.

The intersection of AI and law is not a single topic but two distinct, orthogonal fields. The 'law of AI' concerns policy and regulation of the technology itself. 'AI and the law' studies how AI tools are transforming the cognitive practice of the legal profession.

AI's integration into democracy isn't happening through top-down mandates but via individual actors like city councilors and judges. They can use AI tools for tasks like drafting bills or interpreting laws without seeking permission, leading to rapid, unregulated adoption in areas with low public visibility.

The economic and societal impact of AI is forcing politicians across the aisle to collaborate. From co-sponsoring legislation on AI-driven job loss to debating state vs. federal regulation, AI is creating common ground for lawmakers who would otherwise rarely work together.

AI development has evolved to where models can be directed using human-like language. Instead of complex prompt engineering or fine-tuning, developers can provide instructions, documentation, and context in plain English to guide the AI's behavior, democratizing access to sophisticated outcomes.

The era of prompt engineering is ending. The future is proactive AI agents working in the background to surface critical information. These agents will automatically monitor for and alert teams to competitor launches, new patent filings, and regulatory changes, shifting from a manual 'pull' to an automated 'push' model of intelligence.

AI agents could negotiate hyper-detailed contracts that account for every possible future eventuality, a theoretical concept currently impossible for humans. This would create a new standard for agreements by replacing legal default rules with bespoke, mutually-optimized terms.

AI tools can instantly parse, reformat, and summarize dense documents like congressional bills, which would otherwise require significant manual cleanup. This capability transforms workflows for analysts and researchers, reallocating time from tedious data preparation to high-value strategic analysis.

In risk-averse sectors like law, AI's ability to automate core, revenue-generating tasks (e.g., writing) acts as the primary driver for innovation. The threat of being made obsolete forces legacy players to embrace technology and new business models they would otherwise ignore or resist.